Chirality-Dependent Kinetics of Single-Walled Carbon Nanotubes from Machine-Learning Force Fields

Abstract

The origin of the chirality of single-walled carbon nanotubes (SWCNTs) has been a long-standing dispute. Molecular dynamics (MD) simulations driven by machine-learning force fields (MLFF), which can study the interface dynamics under near ab-initio accuracy, provides a powerful technique to reveal the formation mechanism of SWCNTs. Here, we develop a cobalt-carbon MLFF and perform growth simulations on a cobalt catalyst to investigate the chirality preference of the growth of SWCNTs under the vapor-liquid-solid (VLS) regime. Through microkinetic modeling, we reproduce the observed growth and defect kinetics, demonstrating their dependence on the chirality. It is observed that while the initial chirality assignment is likely related to the configurational degeneracy of the nanotube caps, pentagon defects immediately form and resolve after nucleation. Such processes, which we name as diameter control mechanisms, not only control the diameter toward an optimum but also shift the chirality distribution drastically. Our work therefore offers a microkinetic modeling workflow for the chirality-dependent kinetics of the SWCNTs, highlighting the important contribution of the defect kinetics to the chirality origination.

10 pages, 7 figures

References in corpus (8)

• DeePMD-kit: A deep learning package for many-body potential energy representation and molecular dynamics
• DP-GEN: A concurrent learning platform for the generation of reliable deep learning based potential energy models
• DeePMD-kit v2: A software package for Deep Potential models
• Why do nanotubes grow chiral?
• Entropy driven stability of chiral single-walled carbon nanotubes
• A Semi-Grand Canonical Kinetic Monte Carlo study of Single-Walled Carbon Nanotubes growth
• Obtaining the long-term behavior of Master equations with finite state space from the structure of the associated state transition network
• Edge Dynamics in Iron-Cluster Catalyzed Growth of Single-Walled Carbon Nanotubes Revealed by Molecular Dynamics Simulations based on a Neural Network Potential

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